Alignment of gene expression profiles from test samples against a reference database: New method for context-specific interpretation of microarray data

Alignment of gene expression profiles from test samples against a reference database: New method for context-specific interpretation of microarray data Kilpinen, Sami K Ojala, Kalle A Kallioniemi, Olli P England BioData mining BioData Min. 2011 Mar 31;4:5. engBACKGROUND: Gene expression microarray data have been organized and made available as public databases, but the utilization of such highly heterogeneous reference datasets in the interpretation of data from individual test samples is not as developed as e.g. in the field of nucleotide sequence comparisons. We have created a rapid and powerful approach for the alignment of microarray gene expression profiles (AGEP) from test samples with those contained in a large annotated public reference database and demonstrate here how this can facilitate interpretation of microarray data from individual samples. METHODS: AGEP is based on the calculation of kernel density distributions for the levels of expression of each gene in each reference tissue type and provides a quantitation of the similarity between the test sample and the reference tissue types as well as the identity of the typical and atypical genes in each comparison. As a reference database, we used 1654 samples from 44 normal tissues (extracted from the Genesapiens database). RESULTS: Using leave-one-out validation, AGEP correctly defined the tissue of origin for 1521 (93.6%) of all the 1654 samples in the original database. Independent validation of 195 external normal tissue samples resulted in 87% accuracy for the exact tissue type and 97% accuracy with related tissue types. AGEP analysis of 10 Duchenne muscular dystrophy (DMD) samples provided quantitative description of the key pathogenetic events, such as the extent of inflammation, in individual samples and pinpointed tissue-specific genes whose expression changed (SAMD4A) in DMD. AGEP analysis of microarray data from adipocytic differentiation of mesenchymal stem cells and from normal myeloid cell types and leukemias provided quantitative characterization of the transcriptomic changes during normal and abnormal cell differentiation. CONCLUSIONS: The AGEP method is a widely applicable method for the rapid comprehensive interpretation of microarray data, as proven here by the definition of tissue- and disease-specific changes in gene expression as well as during cellular differentiation. The capability to quantitatively compare data from individual samples against a large-scale annotated reference database represents a widely applicable paradigm for the analysis of all types of high-throughput data. AGEP enables systematic and quantitative comparison of gene expression data from test samples against a comprehensive collection of different cell/tissue types previously studied by the entire research community.Peer reviewe

Bacterial Biogeography of the Colon in Dogs With Chronic Inflammatory Enteropathy

The intestinal microbiota is believed to play a role in the pathogenesis of inflammatory bowel disease in humans and chronic inflammatory enteropathy (CIE) in dogs. While most previous studies have described the gut microbiota using sequencing methods, it is fundamental to assess the spatial distribution of the bacteria for a better understanding of their relationship with the host. The microbiota in the colonic mucosa of 22 dogs with CIE and 11 control dogs was investigated using fluorescence in situ hybridization (FISH) with a universal eubacterial probe (EUB338) and specific probes for select bacterial groups. The number of total bacteria labeled with EUB338 probe was lower within the colonic crypts of dogs with CIE compared to controls. Helicobacter spp. and Akkermansia spp. were decreased on the colonic surface and in the crypts of dogs with CIE. Dogs with CIE had increased number of Escherichia coli/Shigella spp. on the colonic surface and within the crypts compared to control dogs. In conclusion, the bacterial microbiota in the colonic mucosa differed between dogs with and without CIE, with depletion of the crypt bacteria in dogs with CIE. The crypt bacterial species that was intimately associated with the host mucosa in control dogs was composed mainly of Helicobacter spp.Peer reviewe

Introducing the INSIGNIA project: environmental monitoring of pesticide use through honey bees

INSIGNIA aims to design and test an innovative, non-invasive, scientifically proven citizen science environmental monitoring protocol for the detection of pesticides by honey bees. It is a 30-month pilot project initiated and financed by the EC (PP-1-1-2018; EC SANTE). The study is being carried out by a consortium of specialists in honey bees, apiculture, statistics, analytics, modelling, extension, social science and citizen science from twelve countries. Honey bee colonies are excellent bio-samplers of biological material such as nectar, pollen and plant pathogens, as well as non-biological material such as pesticides or airborne contamination. Honey bee colonies forage over a circle of 1 km radius, increasing to several km if required, depending on the availability and attractiveness of food. All material collected is accumulated in the hive.The honey bee colony can provide four main matrices for environmental monitoring: bees, honey, pollen and wax. Because of the non-destructive remit of the project, for pesticides, pollen is the focal matrix and used as trapped pollen and beebread in this study. Although beeswax can be used as a passive sampler for pesticides, this matrix is not being used in INSIGNIA because of its polarity dependent absorbance, which limits the required wide range of pesticides to be monitored. Alternatively, two innovative non-biological matrices are being tested: i) the “Beehold tube”, a tube lined with the generic absorbent polyethylene-glycol PEG, through which hive-entering bees are forced to pass, and ii) the “APIStrip” (Absorbing Pesticides In-hive Strips) with a specific pesticide absorbent which is hung between the bee combs.Beebread and pollen collected in pollen traps are being sampled every two weeks to be analysed for pesticide residues and to record foraging conditions. Trapped pollen provides snapshots of the foraging conditions and contaminants on a single day. During the active season, the majority of beebread is consumed within days, so beebread provides recent, random sampling results. The Beehold tube and the APIStrips are present throughout the 2-weeks sampling periods in the beehive, absorbing and accumulating the incoming contaminants. The four matrices i.e. trapped pollen, beebread, Beehold tubes and APIStrips will be analysed for the presence of pesticides. The botanical origin of trapped pollen, beebread and pollen in the Beehold tubes will also be determined with an innovative molecular technique. Data on pollen and pesticide presence will then be combined to obtain information on foraging conditions and pesticide use, together with evaluation of the CORINE database for land use and pesticide legislation to model the exposure risks to honey bees and wild bees. All monitoring steps from sampling through to analysis will be studied and rigorously tested in four countries in Year 1, and the best practices will then be ring-tested in nine countries in Year 2. Information about the course of the project, its results and publications will be available on the INSIGNIA website www.insignia-bee.eu and via social media: on Facebook (https://www.facebook.com/insigniabee.eu/); Instagram insignia_bee); and Twitter (insignia_bee). Although the analyses of pesticide residues and pollen identification will not be completed until December 2019, in my talk I will present preliminary results of the Year 1 sampling.info:eu-repo/semantics/publishedVersio

Coupling early warning services, crowdsourcing, and modelling for improved decision support and wildfire emergency management

The threat of a forest fire disaster increases around the globe as the human footprint continues to encroach on natural areas and climate change effects increase the potential of extreme weather. It is essential that the tools to educate, prepare, monitor, react, and fight natural fire disasters are available to emergency managers and responders and reduce the overall disaster effects. In the context of the I-REACT project, such a big crisis data system is being developed and is based on the integration of information from different sources, automated data processing chains and decision support systems. This paper presents the wildfire monitoring for emergency management system for those involved and affected by wildfire disasters developed for European forest fire disasters

Multi-Class Clustering of Cancer Subtypes through SVM Based Ensemble of Pareto-Optimal Solutions for Gene Marker Identification

With the advancement of microarray technology, it is now possible to study the expression profiles of thousands of genes across different experimental conditions or tissue samples simultaneously. Microarray cancer datasets, organized as samples versus genes fashion, are being used for classification of tissue samples into benign and malignant or their subtypes. They are also useful for identifying potential gene markers for each cancer subtype, which helps in successful diagnosis of particular cancer types. In this article, we have presented an unsupervised cancer classification technique based on multiobjective genetic clustering of the tissue samples. In this regard, a real-coded encoding of the cluster centers is used and cluster compactness and separation are simultaneously optimized. The resultant set of near-Pareto-optimal solutions contains a number of non-dominated solutions. A novel approach to combine the clustering information possessed by the non-dominated solutions through Support Vector Machine (SVM) classifier has been proposed. Final clustering is obtained by consensus among the clusterings yielded by different kernel functions. The performance of the proposed multiobjective clustering method has been compared with that of several other microarray clustering algorithms for three publicly available benchmark cancer datasets. Moreover, statistical significance tests have been conducted to establish the statistical superiority of the proposed clustering method. Furthermore, relevant gene markers have been identified using the clustering result produced by the proposed clustering method and demonstrated visually. Biological relationships among the gene markers are also studied based on gene ontology. The results obtained are found to be promising and can possibly have important impact in the area of unsupervised cancer classification as well as gene marker identification for multiple cancer subtypes

Genetic determinants of co-accessible chromatin regions in activated T cells across humans.

Over 90% of genetic variants associated with complex human traits map to non-coding regions, but little is understood about how they modulate gene regulation in health and disease. One possible mechanism is that genetic variants affect the activity of one or more cis-regulatory elements leading to gene expression variation in specific cell types. To identify such cases, we analyzed ATAC-seq and RNA-seq profiles from stimulated primary CD4+ T cells in up to 105 healthy donors. We found that regions of accessible chromatin (ATAC-peaks) are co-accessible at kilobase and megabase resolution, consistent with the three-dimensional chromatin organization measured by in situ Hi-C in T cells. Fifteen percent of genetic variants located within ATAC-peaks affected the accessibility of the corresponding peak (local-ATAC-QTLs). Local-ATAC-QTLs have the largest effects on co-accessible peaks, are associated with gene expression and are enriched for autoimmune disease variants. Our results provide insights into how natural genetic variants modulate cis-regulatory elements, in isolation or in concert, to influence gene expression

Introducing the INSIGNIA project: Environmental monitoring of pesticides use through honey bees

INSIGNIA aims to design and test an innovative, non-invasive, scientifically proven citizen science environmental monitoring protocol for the detection of pesticides via honey bees. It is a pilot project initiated and financed by the European Commission (PP-1-1-2018; EC SANTE). The study is being carried out by a consortium of specialists in honey bees, apiculture, chemistry, molecular biology, statistics, analytics, modelling, extension, social science and citizen science from twelve countries. Honey bee colonies are excellent bio-samplers of biological material such as nectar, pollen and plant pathogens, as well as non-biological material such as pesticides or airborne contamination. Honey bee colonies forage over a circle of about 1 km radius, increasing to several km if required depending on the availability and attractiveness of food. All material collected is concentrated in the hive, and the honey bee colony can provide four main matrices for environmental monitoring: bees, honey, pollen and wax. For pesticides, pollen and wax are the focal matrices. Pollen collected in pollen traps will be sampled every two weeks to record foraging conditions. During the season, most of pollen is consumed within days, so beebread can provide recent, random sampling results. On the other hand wax acts as a passive sampler, building up an archive of pesticides that have entered the hive. Alternative in-hive passive samplers will be tested to replicate wax as a “pesticide-sponge”. Samples will be analysed for the presence of pesticides and the botanical origin of the pollen using an ITS2 DNA metabarcoding approach. Data on pollen and pesticides will be then be combined to obtain information on foraging conditions and pesticide use, together with evaluation of the CORINE database for land use and pesticide legislation to model the exposure risks to honey bees and wild bees. All monitoring steps from sampling through to analysis will be studied and tested in four countries in year 1, and the best practices will then be ring-tested in nine countries in year 2. Information about the course of the project and its results and publications will be available in the INSIGNIA website www.insignia-bee.eu.info:eu-repo/semantics/publishedVersio

How Do Honeybees Attract Nestmates Using Waggle Dances in Dark and Noisy Hives?

It is well known that honeybees share information related to food sources with nestmates using a dance language that is representative of symbolic communication among non-primates. Some honeybee species engage in visually apparent behavior, walking in a figure-eight pattern inside their dark hives. It has been suggested that sounds play an important role in this dance language, even though a variety of wing vibration sounds are produced by honeybee behaviors in hives. It has been shown that dances emit sounds primarily at about 250–300 Hz, which is in the same frequency range as honeybees' flight sounds. Thus the exact mechanism whereby honeybees attract nestmates using waggle dances in such a dark and noisy hive is as yet unclear. In this study, we used a flight simulator in which honeybees were attached to a torque meter in order to analyze the component of bees' orienting response caused only by sounds, and not by odor or by vibrations sensed by their legs. We showed using single sound localization that honeybees preferred sounds around 265 Hz. Furthermore, according to sound discrimination tests using sounds of the same frequency, honeybees preferred rhythmic sounds. Our results demonstrate that frequency and rhythmic components play a complementary role in localizing dance sounds. Dance sounds were presumably developed to share information in a dark and noisy environment

Restored in vivo-like membrane lipidomics positively influence in vitro features of cultured mesenchymal stromal/stem cells derived from human placenta

BACKGROUND: The study of lipid metabolism in stem cell physiology has recently raised great interest. The role of lipids goes beyond the mere structural involvement in assembling extra- and intra-cellular compartments. Nevertheless, we are still far from understanding the impact of membrane lipidomics in stemness maintenance and differentiation patterns. In the last years, it has been reported how in vitro cell culturing can modify membrane lipidomics. The aim of the present work was to study the membrane fatty acid profile of mesenchymal stromal cells (MSCs) derived from human fetal membranes (hFM-MSCs) and to correlate this to specific biological properties by using chemically defined tailored lipid supplements (Refeed®). METHODS: Freshly isolated hFM-MSCs were characterized for their membrane fatty acid composition. hFM-MSCs were cultivated in vitro following a classical protocol and their membrane fatty acid profile at different passages was compared to the profile in vivo. A tailored Refeed® lipid supplement was developed with the aim of reducing the differences created by the in vitro cultivation and was tested on cultured hFM-MSCs. Cell morphology, viability, proliferation, angiogenic differentiation, and immunomodulatory properties after in vitro exposure to the tailored Refeed® lipid supplement were investigated. RESULTS: A significant modification of hFM-MSC membrane fatty acid composition occurred during in vitro culture. Using a tailored lipid supplement, the fatty acid composition of cultured cells remained more similar to their in vivo counterparts, being characterized by a higher polyunsaturated and omega-6 fatty acid content. These changes in membrane composition had no effect on cell morphology and viability, but were linked with increased cell proliferation rate, angiogenic differentiation, and immunomodulatory properties. In particular, Refeed®-supplemented hFM-MSCs showed greater ability to express fully functional cell membrane molecules. CONCLUSIONS: Culturing hFM-MSCs alters their fatty acid composition. A tailored lipid supplement is able to improve in vitro hFM-MSC functional properties by recreating a membrane environment more similar to the physiological counterpart. This approach should be considered in cell therapy applications in order to maintain a higher cell quality during in vitro passaging and to influence the outcome of cell-based therapeutic approaches when cells are administered to patients